Modelling headloss and two-step denitrification in a full-scale wastewater post-denitrifying biofiltration plant
Bibliographic record
Abstract
The NO3−/NO2− removal and headloss evolution behaviour of a post-denitrification wastewater biofiltration stage using methanol as an external carbon source was modelled. Three datasets collected on different time scales and at different locations on a full-size plant from the Paris conurbation (800 000 population equivalent) were used in this study. The model was first calibrated on a short-term experiment, during which a shift in the methanol to NOX ratio was imposed at the influent of a treatment lane. Measurements were taken at different frequencies at the effluent as well as at different heights inside the media bed. The model was then used on a 240-day period in 2008 to simulate the behaviour of the whole denitrification stage. Results were good overall for most simulated variables, although nitrite was overestimated for the long-term dataset. Results showed that the model is highly sensitive to variations on the amounts of methanol injected during treatment, especially regarding nitrite and headloss.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".